Preventive Care

A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide.

BACKGROUND: The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is delivered by improving care processes and patient outcomes. Research on the clinical and organisational benefits of artificial intelligence is still at an ...

The Machine Learning Model for Predicting Inadequate Bowel Preparation Before Colonoscopy: A Multicenter Prospective Study.

INTRODUCTION: Colonoscopy is a critical diagnostic tool for colorectal diseases; however, its effectiveness depends on adequate bowel preparation (BP). This study aimed to develop a machine learning predictive model based on Chinese adults for inadequate BP.

Research on a machine learning-based adaptive and efficient screening model for psychological symptoms of community correctional prisoners.

Community correction institutions in China frequently employ the Symptom Checklist-90 (SCL-90) and the health survey brief (SF-12) as primary tools fo...

Application of machine learning for high-throughput tumor marker screening.

High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk ...

Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.

Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recur...

UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images.

Colorectal cancer (CRC) stands out as one of the most prevalent global cancers. The accurate localization of colorectal polyps in endoscopy images is ...

Ontological representation, modeling, and analysis of parasite vaccines.

BACKGROUND: Pathogenic parasites are responsible for multiple diseases, such as malaria and Chagas disease, in humans and livestock. Traditionally, pa...

Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.

The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk...

Applying Artificial Intelligence for Phenotyping of Inherited Arrhythmia Syndromes.

Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particularly among young individuals. Recent advances in ...

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.

BACKGROUND: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large s...

Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review.

This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of p...

General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in societ...

Application of parallel artificial membrane permeability assay technique and chemometric modeling for blood-brain barrier permeability prediction of protein kinase inhibitors.

This study aims to investigate the passive diffusion of protein kinase inhibitors through the blood-brain barrier (BBB) and to develop a model for th...

Vibrational spectroscopy coupled with machine learning sheds light on the cellular effects induced by rationally designed TLR4 agonists.

In this work, we present the potential of Fourier transform infrared (FTIR) microspectroscopy to compare on whole cells, in an unbiased and untargeted...

Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).

BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowe...

Assessing portfolio diversification via two-sample graph kernel inference. A case study on the influence of ESG screening.

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rule...

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for improving patient care. This study contributes to thi...

A novel machine learning model for breast cancer detection using mammogram images.

The most fatal disease affecting women worldwide now is breast cancer. Early detection of breast cancer enhances the likelihood of a full recovery and...

The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

Cervical cancer (CC) continues to be a major worldwide health concern, profoundly impacting the lives of countless females worldwide. In low- and midd...

Development and validation of an imageless machine-learning algorithm for the initial screening of prostate cancer.

PURPOSE: Prostate specific antigen (PSA) testing is a low-cost screening method for prostate cancer (PCa). However, its accuracy is limited. While pro...